1. The Manufacturing Quality Implications of Collocating R&D and Manufacturing John Gray The Ohio State University Enno Siemsen University of Minnesota Gurneeta Vasudeva University of Minnesota

2. Collocating Manufacturing and R&D Are there inherent on- going manufacturing performance advantages to collocation with R&D? Alternatively, are there disadvantages to manufacturing due to less “focus”? What are key moderators to any relationship between R&D- manufacturing collocation and manufacturing performance? Collocated Plant, Bristol Myers Squibb, Syracuse NY Manufacturing Plant, Bristol Myers Squibb, New Brunswick NJ R&D Site, Bristol Myers Squibb, Princeton NJ

3. HYPOTHESES

4. First-Order Effect of Collocation: Competing Hypotheses H1a vs. H1b

5. Manufacturing Involvement Problem Solving Activities Product Lifecycle DevelopmentRamp-UpFull-Scale Production R&D Involvement Creating a Manufacturable Design Rapid Prototyping Parallel Process Development Global Search Prototype -> Product Robust Scaling Know Why Transfer Quality Improvement Troubleshooting Supplier/Engineering Changes

6. Concurrent Engineering R&D Manu- facturing “Nowhere in a company is the need for coordination more acute than between the people who are responsible for product design and those responsible for manufacturing.” (Dean and Susman 1989)

7. Logic  H1a Manufacturing and R&D are interdependent throughout the life cycle There are benefits from integrating these activities Distance reduces integration; Collocation is one Integration Mechanism Collocated plants have better manufacturing quality performance than non-collocated plants (H1a)

8. The Drawbacks of Collocation A site is focused “to the extent that it limits the set of conflicting (…) activities in which workers and managers are engaged.” (Huckman and Zinner 2008) More complexity Managerial inattention Diverging incentives Less Specialization Cognitive overload

9. Focus R&D Manu- facturing “The essence of effective production management is stability, efficiency, discipline and tight control, whereas effective R&D management requires dynamism, flexibility, creativity, and loose control.” (Clark and Fujimoto1999)

10. Logic  H1b Manufacturing and R&D are different activities, with different personnel, objectives, etc. Collocating such activities may hinder manufacturing’s focus on its main task Loss of focus can hinder performance Collocated plants have worse manufacturing quality performance than non-collocated plants (H1b)

11. Interaction Effects (H2) Collocation is more beneficial for large companies –Dynamic capabilities to manage subtle challenges of collocated plants Larger pool of professional managers More experience in managing unfocused operations (H3) Collocation is more beneficial for more complex processes –Low complexity means little interdependence –Less tacit knowledge involved

12. DATA

13. Databases FDA Establishment Inspections Delphion Patent Database COMPUSTAT ORBIS Census National Establishment Time Series Thomson, Google

14. Measures Dependent Variable –FDA District Decision Inspection Outcomes (1994-2007) Independent Variables –Collocation (Delphion Patents) –Company Size (Compustat) –Industry Classification (ORBIS)

15. Control Variables Inspection Level, e.g. –Inspection type –Previous inspection outcome –Time since last inspection (Anand, Gray, & Siemsen 2011) Plant Level, e.g. –Plant Type (NETS) –Population Density (Census) –Plant Age (NETS + Search) –Cluster (FDA + geospatial plot) Company Level, e.g. –R&D Intensity (Compustat) –Capital Intensity (Compustat) –Inventory Turns (Compustat) –Tobin’s Q (Compustat)

16. Breadth vs. Depth Original FDA Dataset 30,000 Inspections in 14,000 sites Cleaned FDA Dataset 8,800 Inspections in 1,250 plants Final Dataset 2,304 Inspections in 292 plants

17. ANALYSIS

18. Model Random effects ordered profit –Two levels: Inspection and Plant Estimated using Stata’s GLLAM

19. Results (control variables omitted) VariableModel 1Model 2Model 3 Firm Size: Medium.12 †.22**.23** Firm Size: Large.03.17.21 † Industry: Basic Pharm-.14-.15-.32** Industry: Other-.21-.20 † -.29 † Collocated-.14*.05.00 Collocated*Med-.29*-.32* Collocated*Large-.38*-.53* Collocated*Basic Pharm.60** Collocated*Other.28 Notes: Higher numbers indicate WORSE conformance quality performance **p<.01, *p<.05, † p<.10 (two-tailed) Omitted firm size is “Small”; Omitted Industry is “Pharmaceutical Preparations” (more complex)

20. Results (control variables omitted) VariableModel 1Model 2Model 3 Firm Size: Medium.12 †.22**.23** Firm Size: Large.03.17.21 † Industry: Basic Pharm-.14-.15-.32** Industry: Other-.21-.20 † -.29 † Collocated-.14*.05.00 Collocated*Med-.29*-.32* Collocated*Large-.38*-.53* Collocated*Basic Pharm.60** Collocated*Other.28 Notes: Higher numbers indicate WORSE conformance quality performance **p<.01, *p<.05, † p<.10 (two-tailed) Omitted firm size is “Small”; Omitted Industry is “Pharmaceutical Preparations” (more complex) H1a supported; H1b “rejected”

21. Results (control variables omitted) VariableModel 1Model 2Model 3 Firm Size: Medium.12 †.22**.23** Firm Size: Large.03.17.21 † Industry: Basic Pharm-.14-.15-.32** Industry: Other-.21-.20 † -.29 † Collocated-.14*.05.00 Collocated*Med-.29*-.32* Collocated*Large-.38*-.53* Collocated*Basic Pharm.60** Collocated*Other.28 Notes: Higher numbers indicate WORSE conformance quality performance **p<.01, *p<.05, † p<.10 (two-tailed) Omitted firm size is “Small”; Omitted Industry is “Pharmaceutical Preparations” (more complex) H2 supported

22. Results (control variables omitted) VariableModel 1Model 2Model 3 Firm Size: Medium.12 †.22**.23** Firm Size: Large.03.17.21 † Industry: Basic Pharm-.14-.15-.32** Industry: Other-.21-.20 † -.29 † Collocated-.14*.05.00 Collocated*Med-.29*-.32* Collocated*Large-.38*-.53* Collocated*Basic Pharm.60** Collocated*Other.28 Notes: Higher numbers indicate WORSE conformance quality performance **p<.01, *p<.05, † p<.10 (two-tailed) Omitted firm size is “Small”; Omitted Industry is “Pharmaceutical Preparations” (more complex) H3 Supported

23. The Effect of Collocation

25. Robustness Tests Ordered Probit with Clustered Errors Product/Process Patents Geographical Sub-Clusters Without Plant Age (Increased Sample) Private Firms (3200 inspections in 577 plants) –Results don’t generalize –Possibly because private firms are small Instrumental Variables Analysis –Stata CMP

26. CONCLUSION

27. Summary of Findings Collocated plants have increased manufacturing quality performance –if they belong to larger companies, –that use more complex manufacturing processes.

28. Contributions Collocation as an integration mechanism Manufacturing benefits of manufacturing and R&D integration –On-going conformance quality performance Establishing key contingencies of collocation’s benefits to manufacturing

29. Future Work Study the effect of time –Has the importance of distance diminished? Communication technologies, standards Study mechanisms to balance collocation benefits and drawbacks Study in other settings –Healthcare: Teaching vs. Non-Teaching Hospitals?

30. Thank You